Machines that are currently available for simultaneous scanning and counting of documents such as paper currency are relatively complex and costly, and relatively large in size. The complexity of such machines can also lead to excessive service and maintenance requirements. These drawbacks have inhibited more widespread use of such machines, particularly in banks and other financial institutions where space is limited in areas where the machines are most needed, such as teller areas. The above drawbacks are particularly difficult to overcome in machines which offer much-needed features such as the ability to scan bills regardless of their orientation relative to the machine or to each other, and the ability to authenticate genuineness and/or denomination of the bills.
A variety of techniques and apparatus have been used to satisfy the requirements of automated currency handling systems. At the lower end of sophistication in this area of technology are systems capable of handling only a specific type of currency, such as a specific dollar denomination, while rejecting all other currency types. At the upper end are complex systems which are capable of identifying and discriminating among and automatically counting multiple currency denominations.
Currency discrimination systems typically employ either magnetic sensing or optical sensing for discriminating among different currency denominations. Magnetic sensing is based on detecting the presence or absence of magnetic ink in portions of the printed indicia on the currency by using magnetic sensors, usually ferrite core-based sensors, and using the detected magnetic signals, after undergoing analog or digital processing, as the basis for currency discrimination. A variety of currency characteristics can be measured using magnetic sensing. These include detection of patterns of changes in magnetic flux, patterns of vertical grid lines in the portrait area of bills, the presence of a security thread, total amount of magnetizable material of a bill, patterns from sensing the strength of magnetic fields along a bill, and other patterns and counts from scanning different portions of the bill such as the area in which the denomination is written out.
The more commonly used optical sensing techniques, on the other hand, are based on detecting and analyzing variations in light reflectance or transmissivity characteristics occurring when a currency bill is illuminated and scanned by a strip of focused light. The subsequent currency discrimination is based on the comparison of sensed optical characteristics with prestored parameters for different currency denominations, while accounting for adequate tolerances reflecting differences among individual bills of a given denomination. A variety of currency characteristics can be measured using optical sensing. These include detection of a bill's density, color, length and thickness, the presence of a security thread and holes, and other patterns of reflectance and transmission. Color detection techniques may employ color filters, colored lamps, and/or dichroic beamsplitters.
In addition to magnetic and optical sensing, other techniques of detecting characteristic information of currency include electrical conductivity sensing, capacitive sensing (such as for watermarks, security threads, thickness, and various dielectric properties) and mechanical sensing (such as for size, limpness, and thickness).
A major obstacle in implementing automated currency discrimination systems is obtaining an optimum compromise between the criteria used to adequately define the characteristic pattern for a particular currency denomination, the time required to analyze test data and compare it to predefined parameters in order to identify the currency bill under scrutiny, and the rate at which successive currency bills may be mechanically fed through and scanned. Even with the use of microprocessors for processing the test data resulting from the scanning of a bill, a finite amount of time is required for acquiring samples and for the process of comparing the test data to stored parameters to identify the denomination of the bill.
Recent currency discriminating systems rely on comparisons between a scanned pattern obtained from a subject bill and sets of stored master patterns for the various denominations among which the system is designed to discriminate. For example, it has been found that scanning U.S. bills of different denominations along a central portion thereof provides scanning patterns sufficiently divergent to enable accurate discrimination between different denominations. Such a discrimination device is disclosed in U.S. Pat. No. 5,295,196. However, currencies of other countries can differ from U.S. currency and from each other in a number of ways. For example, while all denominations of U.S. currencies are the same size, in many other countries currencies vary in size by denomination. Furthermore, there is a wide variety of bill sizes among different countries. In addition to size, the color of currency can vary by country and by denomination. Likewise, many other characteristics may vary between bills from different countries and of different denominations.
As a result of the wide variety of currencies used throughout the world, a discrimination system designed to handle bills of one country generally can not handle bills from another country. Likewise, the method of discriminating bills of different denominations of one country may not be appropriate for use in discriminating bills of different denominations of another country. For example, scanning for a given characteristic pattern along a certain portion of bills of one country, such as optical reflectance about the central portion of U.S. bills, may not provide optimal discrimination properties for bills of another country, such as German marks.
Furthermore, there is a distinct need for an identification system which is capable of accepting bills of a number of currency systems, that is, a system capable of accepting a number of bill-types. For example, a bank in Europe may need to process on a regular basis French, British, German, Dutch, etc. currency, each having a number of different denomination values.
Furthermore, in currency discriminating systems that rely on comparisons between a scanned pattern obtained from a subject bill and sets of stored master patterns, the ability of a system to accurately line up the scanned patterns to the master patterns to which they are being compared is important to the ability of a discrimination system to discriminate among bills of various denominations as well as between genuine bills and counterfeit bills without rejecting an unacceptable number of genuine bills. However, the ability of a system to line up scanned and master patterns is often hampered by the improper initiation of the scanning process which results in the generation of scanned patterns. If the generation of scanned patterns is initiated too early or too late, the resulting pattern will not correlate well with the master pattern associated with the identity of the currency; and as a result, a genuine bill may be rejected. There are a number of reasons why a discrimination system may initiate the generation of a scanned pattern too early or too late, for example, stray marks on a bill, the bleeding through of printed indicia from one bill in a stack onto an adjacent bill, the misdetection of the beginning of the area of the printed indicia which is desired to be scanned, and the reliance on the detection of the edge of a bill as the trigger for the scanning process coupled with the variance, from bill to bill, of the location of printed indicia relative to the edge of a bill. Therefore, there is a need to overcome the problems associated with correlating scanned and master patterns.